Overview
The value-added education courses aim to provide additional learner centric graded skill oriented technical training, with the primary objective of improving the employability skills of students.
This course introduces students to classical and modern optimization techniques using MATLAB-Simulink integration for
engineering applications. It covers problem formulation, optimization toolbox functions, and metaheuristic algorithms
such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Harris Hawks
Optimization (HHO). The course emphasizes hands-on implementation, convergence analysis, controller tuning, and
simulation-based optimization for applications in engineering.
Optimization_Techniques_using_MATLAB-Simulink_Integration_NV36111.pdf
Objectives of Event
The course is designed to provide students with a comprehensive understanding of classical and modern optimization
techniques for engineering applications. The course aims to develop the ability to formulate optimization problems,
implement optimization algorithms using MATLAB, and integrate these algorithms with Simulink models for real-time
engineering analysis. Students will gain hands-on experience in applying optimization methods such as Genetic
Algorithm, Particle Swarm Optimization, Grey Wolf Optimization, and Harris Hawks Optimization to control, power, and
signal processing systems. The course also focuses on convergence analysis, parameter tuning, and performance
evaluation of optimization algorithms, enabling students to develop simulation-based solutions suitable for research,
industrial applications, and advanced engineering design.
Convener Details
- Prof. (Dr.) Pallavi Gupta (Dean SSES)
- Dr. Usha Tiwari (Hod EECE)
Co-ordinators:
- Dr. Sabyaasachi Mukaherjee, Department of Electrical Electronics and Communication Engineering, SSES, Sharda University.
